Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach

Zhang, Feng‐Liang; Xiong, Haibei; Shi, Weixing; Ou, Xiaoying

doi:10.1002/stc.1840

Cited by 110 publications

(69 citation statements)

References 40 publications

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“…Here, we focus on the uncertainty law of operational modal analysis (OMA), which aims at identifying the modal parameters (e.g., modal frequencies, damping ratios, and mode shapes) of a structure using ambient vibration data . Because the excitation history is not measured in OMA, modal parameters are identified with large uncertainties; thus, it is of critical importance to quantify them . By introducing frequentist concept in the data (assuming the existence of actual parameter value), the uncertainty law (leading order term of posterior uncertainty) goes one more step to understand the identification uncertainty, providing the achievable identification precision and guiding the design of test configuration.…”

Section: Operational Modal Analysismentioning

confidence: 99%

Posterior uncertainty, asymptotic law and Cramér-Rao bound

2017

Struct Control Health Monit

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Summary In a globally identifiable Bayesian system identification problem, the uncertainty of model parameters can be quantified by their “posterior covariance matrix” calculated for a particular data set. When the data is modeled to be distributed as the likelihood function (i.e., no modeling error), a statistical law analogous to the law of large numbers results, where the posterior covariance matrix is asymptotic to a deterministic quantity that depends on the “information content” of data rather than its particular (stochastic) details. This was referred as the “uncertainty law” in a recent study of the achievable precision of modal parameters in operational modal analysis (OMA). Deriving the uncertainty law involves asymptotics techniques and leveraging on the mathematical structure of the likelihood function, which was found to be tedious. As a sequel to the development, this work shows that for long data and up to a Gaussian approximation of the posterior distribution, the uncertainty law is asymptotic to the inverse of the Fisher information matrix, which coincides with the tightest Cramér‐Rao bound in classical statistics. A parametric study is presented to illustrate the theoretical results in the context of OMA. As a direct application with practical relevance, the relationship provides a systematic means for deriving the uncertainty laws in OMA. Applied and interpreted properly, the posterior covariance matrix (for given data), uncertainty law, and Cramér‐Rao bound can provide a powerful means for quantifying and managing the uncertainties in structural health monitoring.

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Section: Operational Modal Analysismentioning

confidence: 99%

Posterior uncertainty, asymptotic law and Cramér-Rao bound

2017

Struct Control Health Monit

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“…The monitoring system consists of four modules: sensory system, data acquisition system, data processing and control system, and structural performance evaluation system. Su et al explained the monitoring system of Shanghai Tower in detail.…”

Section: Field Informationmentioning

confidence: 99%

Dynamic performance evaluation of Shanghai Tower under winds based on full‐scale data

Zhang

2019

Structural Design Tall Build

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Summary Shanghai Tower is the tallest building in China with a height of 632 m. This study aims to investigate the wind characteristics and its impact on Shanghai Tower so as to provide useful information for the wind‐resistant design of 600 m+ super‐tall buildings. By analyzing the data of wind speed during the occurrence of DeHong in June 2017, the relationship between turbulence intensity and mean wind speed is verified, and the correlation between gust factor and turbulence intensity is confirmed. Apart from that, it is also found that the von Karman spectrum fits well with the measured fluctuating wind speed spectrum. In addition, the 83rd and 117th acceleration data are analyzed to obtain the natural frequency by peak‐picking, frequency domain decomposition, stochastic subspace identification, and fast Bayesian fast Fourier transform methods. The amplitude‐dependence dynamic parameters of Shanghai Tower on the basis of the field measurements are studied as well. Finally, the wind‐induced vibration is investigated based on the acceleration data and wind speed data, which verifies that the responses along two main axes having a similar amplitude under wind effects. The occurrence of DeHong demonstrates that a gale equivalent to a typhoon may occur in urban areas without any urban warning.

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“…Data from these tests were used to determine the natural frequencies and the damping ratios but not mode shapes. After the main tower was completed in 2014, an ambient vibration test of a typical floor was performed to investigate its modal properties . In May of 2015, a more extensive test was conducted to determine the modes shapes and modal frequencies and damping of the completed structure.…”

Section: Field Vibration Test and Shake Table Testmentioning

confidence: 99%

Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach

Zhang

Ventura

Xiong

et al. 2017

Struct Control Health Monit

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Summary The Shanghai Tower is a newly built 127‐story and 632 m high super tall building. As of April 2017, it was ranked as the second tallest building in the world. Its main structural system is a mega‐frame‐tube‐outrigger system with six outrigger trusses along the height. Due to its unique structural configuration, a series of field and laboratory model tests have been conducted to better understand its dynamic characteristics. Before its construction, a scaled model of the tower was tested on a shake table, and the results were used to refine the design of the tower. At the completion of the construction, full‐scale ambient vibration tests were performed. A Bayesian method was used to perform operational modal analysis from the shake table and full‐scale ambient vibration tests. The most probable value of the modal parameters and the associated posterior uncertainties were calculated using this method. The first eight modes were identified, including three translational modes in each principal direction and two torsional modes. Using these results, the dynamic characteristics and associated uncertainties obtained from the two tests were investigated and compared in this paper. Due to the scaling of the model, there are some discrepancies between the natural frequencies obtained from two different tests, but the identified mode shapes matched very well. Although the structure was designed in a very innovative manner, its dynamic characteristics are similar to regular tall buildings. The results from this investigation provide valuable information for an ongoing condition assessment of this super tall building.

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Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach

Cited by 110 publications

References 40 publications

Posterior uncertainty, asymptotic law and Cramér-Rao bound

Posterior uncertainty, asymptotic law and Cramér-Rao bound

Dynamic performance evaluation of Shanghai Tower under winds based on full‐scale data

Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach

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